Stochastic optimal foraging theory

Abstract

We present here the core elements of a stochastic optimal foraging theory (SOFT), essentially, a random search theory for ecologists. SOFT complements classic optimal foraging theory (OFT) in that it assumes fully uninformed searchers in an explicit space. Mathematically, the theory quantifies the time spent by a random walker (the forager) on a spatial region delimited by absorbing boundaries (the targets). The walker starts from a given initial position and has no previous knowledge (nor the possibility to gain knowledge) on target/patch locations. Averages on such process can describe the dynamics of an uninformed forager looking for successive targets in a diverse and dynamical spatial environment. The framework provides a means to advance in the study of search uncertainty and animal information use in natural foraging systems. © 2013 Springer-Verlag Berlin Heidelberg.